2,983 research outputs found
Weighted Random Popular Matchings
For a set A of n applicants and a set I of m items, we consider a problem of
computing a matching of applicants to items, i.e., a function M mapping A to I;
here we assume that each applicant provides a preference list on
items in I. We say that an applicant prefers an item p than an item q
if p is located at a higher position than q in its preference list, and we say
that x prefers a matching M over a matching M' if x prefers M(x) over M'(x).
For a given matching problem A, I, and preference lists, we say that M is more
popular than M' if the number of applicants preferring M over M' is larger than
that of applicants preferring M' over M, and M is called a popular matching if
there is no other matching that is more popular than M. Here we consider the
situation that A is partitioned into , and that each
is assigned a weight such that w_{1}>w_{2}>...>w_{k}>0m/n^{4/3}=o(1)w_{1} \geq 2w_{2}n^{4/3}/m = o(1)w_{1} \geq 2w_{2}$ has a 2-weighted popular
matching with probability 1-o(1).Comment: 13 pages, 2 figure
Popular Matchings in the Weighted Capacitated House Allocation Problem
We consider the problem of finding a popular matching in the Weighted Capacitated
House Allocation problem (WCHA). An instance of WCHA involves a set of agents
and a set of houses. Each agent has a positive weight indicating his priority, and a
preference list in which a subset of houses are ranked in strict order. Each house has
a capacity that indicates the maximum number of agents who could be matched to
it. A matching M of agents to houses is popular if there is no other matching M′
such that the total weight of the agents who prefer their allocation in M′
to that in
M exceeds the total weight of the agents who prefer their allocation in M to that in
M′
. Here, we give an O(
√
Cn1 + m) algorithm to determine if an instance of WCHA
admits a popular matching, and if so, to find a largest such matching, where C is the
total capacity of the houses, n1 is the number of agents, and m is the total length of
the agents’ preference lists
Popular matchings in the weighted capacitated house allocation problem
We consider the problem of finding a popular matching in the <i>Weighted Capacitated House Allocation</i> problem (WCHA). An instance of WCHA involves a set of agents and a set of houses. Each agent has a positive weight indicating his priority, and a preference list in which a subset of houses are ranked in strict order. Each house has a capacity that indicates the maximum number of agents who could be matched to it. A matching M of agents to houses is popular if there is no other matching M′ such that the total weight of the agents who prefer their allocation in M′ to that in M exceeds the total weight of the agents who prefer their allocation in M to that in M′. Here, we give an [FORMULA] algorithm to determine if an instance of WCHA admits a popular matching, and if so, to find a largest such matching, where C is the total capacity of the houses, n1 is the number of agents, and m is the total length of the agents' preference lists
Counting Popular Matchings in House Allocation Problems
We study the problem of counting the number of popular matchings in a given
instance. A popular matching instance consists of agents A and houses H, where
each agent ranks a subset of houses according to their preferences. A matching
is an assignment of agents to houses. A matching M is more popular than
matching M' if the number of agents that prefer M to M' is more than the number
of people that prefer M' to M. A matching M is called popular if there exists
no matching more popular than M. McDermid and Irving gave a poly-time algorithm
for counting the number of popular matchings when the preference lists are
strictly ordered.
We first consider the case of ties in preference lists. Nasre proved that the
problem of counting the number of popular matching is #P-hard when there are
ties. We give an FPRAS for this problem.
We then consider the popular matching problem where preference lists are
strictly ordered but each house has a capacity associated with it. We give a
switching graph characterization of popular matchings in this case. Such
characterizations were studied earlier for the case of strictly ordered
preference lists (McDermid and Irving) and for preference lists with ties
(Nasre). We use our characterization to prove that counting popular matchings
in capacitated case is #P-hard
Rank Maximal Matchings -- Structure and Algorithms
Let G = (A U P, E) be a bipartite graph where A denotes a set of agents, P
denotes a set of posts and ranks on the edges denote preferences of the agents
over posts. A matching M in G is rank-maximal if it matches the maximum number
of applicants to their top-rank post, subject to this, the maximum number of
applicants to their second rank post and so on.
In this paper, we develop a switching graph characterization of rank-maximal
matchings, which is a useful tool that encodes all rank-maximal matchings in an
instance. The characterization leads to simple and efficient algorithms for
several interesting problems. In particular, we give an efficient algorithm to
compute the set of rank-maximal pairs in an instance. We show that the problem
of counting the number of rank-maximal matchings is #P-Complete and also give
an FPRAS for the problem. Finally, we consider the problem of deciding whether
a rank-maximal matching is popular among all the rank-maximal matchings in a
given instance, and give an efficient algorithm for the problem
Popular matchings in the marriage and roommates problems
Popular matchings have recently been a subject of study in the context of the so-called House Allocation Problem, where the objective is to match applicants to houses over which the applicants have preferences. A matching M is called popular if there is no other matching M′ with the property that more applicants prefer their allocation in M′ to their allocation in M. In this paper we study popular matchings in the context of the Roommates Problem, including its special (bipartite) case, the Marriage Problem. We investigate the relationship between popularity and stability, and describe efficient algorithms to test a matching for popularity in these settings. We also show that, when ties are permitted in the preferences, it is NP-hard to determine whether a popular matching exists in both the Roommates and Marriage cases
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